Dependable Navigation for Multiple Autonomous Robots with Petri Nets Based Congestion Control and Dynamic Obstacle Avoidance

被引:0
|
作者
Lan Anh Trinh
Mikael Ekström
Baran Cürüklü
机构
[1] Malardalen University,School of Innovation, Design and Engineer
来源
关键词
Dependable path planning; Dipole field; Obstacle avoidance; Congestion control;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper, a novel path planning algorithm for multiple robots using congestion analysis and control is presented. The algorithm ensures a safe path planning solution by avoiding collisions among robots as well as among robots and humans. For each robot, alternative paths to the goal are realised. By analysing the travelling time of robots on different paths using Petri Nets, the optimal configuration of paths is selected. The prime objective is to avoid congestion when routing many robots into a narrow area. The movements of robots are controlled at every intersection by organising a one-by-one passing of the robots. Controls are available for the robots which are able to communicate and share information with each other. To avoid collision with humans and other moving objects (i.e. robots), a dipole field integrated with a dynamic window approach is developed. By considering the velocity and direction of the dynamic obstacles as sources of a virtual magnetic dipole moment, the dipole-dipole interaction between different moving objects will generate repulsive forces proportional to the velocity to prevent collisions. The whole system is presented on the widely used platform Robot Operating System (ROS) so that its implementation is extendable to real robots. Analysis and experiments are demonstrated with extensive simulations to evaluate the effectiveness of the proposed approach.
引用
收藏
相关论文
共 50 条
  • [21] Advanced Control Algorithms for Dynamic Environment Navigation and Obstacle Avoidance
    A. Y. Nour Alsayed
    undefined Krasnov
    Gyroscopy and Navigation, 2024, 15 (3) : 281 - 295
  • [22] Obstacle avoidance control for mobile robots based on vision
    Nara, Shunsuke
    Takahashi, Satoru
    2006 SICE-ICASE INTERNATIONAL JOINT CONFERENCE, VOLS 1-13, 2006, : 3470 - +
  • [23] Autonomous Visual Navigation and Laser-Based Moving Obstacle Avoidance
    Cherubini, Andrea
    Spindler, Fabien
    Chaumette, Francois
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2014, 15 (05) : 2101 - 2110
  • [24] Visual Navigation and Obstacle Avoidance Control for Agricultural Robots via LiDAR and Camera
    Han, Chongyang
    Wu, Weibin
    Luo, Xiwen
    Li, Jiehao
    REMOTE SENSING, 2023, 15 (22)
  • [25] Autonomous Quadrotor Navigation With Vision Based Obstacle Avoidance and Path Planning
    Lin, Huei-Yung
    Peng, Xin-Zhong
    IEEE ACCESS, 2021, 9 : 102450 - 102459
  • [26] Template-based autonomous navigation and obstacle avoidance in urban environments
    Souza, Jefferson R.
    Sales, Daniel O.
    Shinzato, Patrick Y.
    Osorio, Fernando S.
    Wolf, Denis F.
    APPLIED COMPUTING REVIEW, 2011, 11 (04): : 49 - 59
  • [27] Decentralized behavior-based formation control of multiple robots considering obstacle avoidance
    Giroung Lee
    Dongkyoung Chwa
    Intelligent Service Robotics, 2018, 11 : 127 - 138
  • [28] Decentralized behavior-based formation control of multiple robots considering obstacle avoidance
    Lee, Giroung
    Chwa, Dongkyoung
    INTELLIGENT SERVICE ROBOTICS, 2018, 11 (01) : 127 - 138
  • [29] Joint Vision-Based Navigation, Control and Obstacle Avoidance for UAVs in Dynamic Environments
    Potena, Ciro
    Nardi, Daniele
    Pretto, Alberto
    2019 EUROPEAN CONFERENCE ON MOBILE ROBOTS (ECMR), 2019,
  • [30] Hybrid system synthesis and control for obstacle avoidance and autonomous maneuvering of mobile robots
    Lee, Y
    Lim, MS
    Lim, J
    PROCEEDINGS OF THE 4TH ASIA-PACIFIC CONFERENCE ON CONTROL & MEASUREMENT, 2000, : 1 - 6